Residential College | false |
Status | 已發表Published |
Iterative Learning enhanced Integral Terminal Sliding Mode Control for Precision Motion Systems | |
Feng, Zhao1; Ling, Jie2; Wan, Feng1; Yang, Zhi Xin3 | |
2021-05-14 | |
Conference Name | 2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS) |
Source Publication | Proceedings of 2021 IEEE 10th Data Driven Control and Learning Systems Conference, DDCLS 2021 |
Pages | 778-783 |
Conference Date | 14-16 May 2021 |
Conference Place | Suzhou, China |
Country | China |
Author of Source | Sun M., Zhang H. |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Abstract | The rapid development and applications of precision motion systems pose a great challenge on tracking performance improvement to complete various industrial or scientific tasks. In this paper, an iterative learning enhanced integral terminal sliding mode control (IL- ITSMC) is developed to further enhance the performance of such systems under repetitive trajectory and disturbance. For the generally used second-order model in precision motion systems, an integral terminal sliding surface is utilized to improve the steady-state performance and robustness to unexpected disturbance. A novel reaching law is also designed to realize the finite-time convergence of the sliding surface. In addition, an iterative learning law is proposed based on the sliding surface to compensate the repetitive term through updating the feedforward control input iteratively. The stability in time domain and convergence in iterative domain are proven theoretically based on the well-known Lyapunov theory, respectively. The simulation results on a pizeo-actuated stage with hysteresis nonlinearity demonstrate that the proposed IL-ITSMC achieves the best tracking performance through comparisons, and the convergence speed is improved significantly in comparison with ITSMC with traditional P-type ILC (PIL- ITSMC) for a 10Hz sinusoidal repetitive trajectory. |
Keyword | Precision Motion Tracking Sliding Mode Control Iterative Learning Control |
DOI | 10.1109/DDCLS52934.2021.9455576 |
URL | View the original |
Indexed By | EI |
Language | 英語English |
Scopus ID | 2-s2.0-85114204185 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU) DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING DEPARTMENT OF ELECTROMECHANICAL ENGINEERING |
Affiliation | 1.Department of Electrical and Computer Engineering, University of Macau, Macao, P. R. China 2.College of Mechanical Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China 3.State Key Laboratory of Internet of Things for Smart City and Department of Electromechanical Engineering, University of Macau, Macao, P. R. China |
First Author Affilication | University of Macau |
Recommended Citation GB/T 7714 | Feng, Zhao,Ling, Jie,Wan, Feng,et al. Iterative Learning enhanced Integral Terminal Sliding Mode Control for Precision Motion Systems[C]. Sun M., Zhang H.:Institute of Electrical and Electronics Engineers Inc., 2021, 778-783. |
APA | Feng, Zhao., Ling, Jie., Wan, Feng., & Yang, Zhi Xin (2021). Iterative Learning enhanced Integral Terminal Sliding Mode Control for Precision Motion Systems. Proceedings of 2021 IEEE 10th Data Driven Control and Learning Systems Conference, DDCLS 2021, 778-783. |
Files in This Item: | There are no files associated with this item. |
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment